Simulation of south Asian physical environment using various cumulus parameterization schemes of MM5

Meteorological applications

article

Sabir Sardar¹  Idrees Ahmad¹  Syed Shoaib Raza¹  Naseem Irfan¹ 

[1] Department of Nuclear Engineering, Pakistan Institute of Engineering and Applied Sciences (PIEAS)

关键词: convective schemes;    mesoscale model;    monsoon precipitation;    numerical modelling;   

DOI  :  10.1002/met.266

学科分类：社会科学、人文和艺术（综合）

来源: Wiley

【 摘 要 】

The objective of this study was to compare the effect of a selected convective parameterized scheme in a mesoscale model on the predicted precipitation using the fifth-generation Mesoscale Model (MM5). Four cumulus parameterization schemes in MM5, the Grell scheme, the Kain–Fritsch scheme, the Anthes–Kuo scheme and the Betts–Miller scheme were tested to predict the monthly accumulated precipitation in a south Asian region of complex topography during the summer monsoon season (July and August) for the years 1998 and 2001. The simulated results of precipitation were compared with the satellite-derived data of the Tropical Rainfall Measuring Mission (TRMM). Comparison of simulated precipitation patterns revealed that the Grell scheme realistically captured the rainfall patterns over the southern plain areas of the region which receive lesser precipitation throughout the year. This scheme was also in good agreement with the TRMM data for lesser amounts of precipitation over northern mountainous areas, though it showed underestimated results for heavy precipitation over the region. The rainfall patterns over the northern mountainous areas were captured well by the Kain–Fritsch scheme for heavy precipitation while this scheme slightly over predicted the precipitation trends in the southern plain areas. The Anthes–Kuo and the Betts–Miller schemes were not able to simulate the rainfall for this complex terrain satisfactorily. The set of physical options used in MM5 for precipitation in this study was also tested for some other meteorological parameters such as ambient temperature, potential temperature, relative humidity and the moist static energy and the results were validated against the Reanalysis data of US National Centre for Environmental Prediction (NCEP). It was found that the scheme that successfully simulated precipitation also predicted these other parameters well.

【 授权许可】

CC BY|CC BY-NC|CC BY-NC-ND